From eaff93d862c9c859d200530744d49e5b401596ce Mon Sep 17 00:00:00 2001
From: Enno Hermann <Eginhard@users.noreply.github.com>
Date: Mon, 6 Jan 2025 13:44:08 +0100
Subject: [PATCH] chore: remove unused callback code (#229)

The callbacks are in trainer.callbacks now
---
 TTS/utils/callbacks.py                        | 105 ------------------
 .../extension/implementing_a_new_model.md     |   2 +-
 2 files changed, 1 insertion(+), 106 deletions(-)
 delete mode 100644 TTS/utils/callbacks.py

diff --git a/TTS/utils/callbacks.py b/TTS/utils/callbacks.py
deleted file mode 100644
index 511d215c65..0000000000
--- a/TTS/utils/callbacks.py
+++ /dev/null
@@ -1,105 +0,0 @@
-class TrainerCallback:
-    @staticmethod
-    def on_init_start(trainer) -> None:
-        if hasattr(trainer.model, "module"):
-            if hasattr(trainer.model.module, "on_init_start"):
-                trainer.model.module.on_init_start(trainer)
-        else:
-            if hasattr(trainer.model, "on_init_start"):
-                trainer.model.on_init_start(trainer)
-
-        if hasattr(trainer.criterion, "on_init_start"):
-            trainer.criterion.on_init_start(trainer)
-
-        if hasattr(trainer.optimizer, "on_init_start"):
-            trainer.optimizer.on_init_start(trainer)
-
-    @staticmethod
-    def on_init_end(trainer) -> None:
-        if hasattr(trainer.model, "module"):
-            if hasattr(trainer.model.module, "on_init_end"):
-                trainer.model.module.on_init_end(trainer)
-        else:
-            if hasattr(trainer.model, "on_init_end"):
-                trainer.model.on_init_end(trainer)
-
-        if hasattr(trainer.criterion, "on_init_end"):
-            trainer.criterion.on_init_end(trainer)
-
-        if hasattr(trainer.optimizer, "on_init_end"):
-            trainer.optimizer.on_init_end(trainer)
-
-    @staticmethod
-    def on_epoch_start(trainer) -> None:
-        if hasattr(trainer.model, "module"):
-            if hasattr(trainer.model.module, "on_epoch_start"):
-                trainer.model.module.on_epoch_start(trainer)
-        else:
-            if hasattr(trainer.model, "on_epoch_start"):
-                trainer.model.on_epoch_start(trainer)
-
-        if hasattr(trainer.criterion, "on_epoch_start"):
-            trainer.criterion.on_epoch_start(trainer)
-
-        if hasattr(trainer.optimizer, "on_epoch_start"):
-            trainer.optimizer.on_epoch_start(trainer)
-
-    @staticmethod
-    def on_epoch_end(trainer) -> None:
-        if hasattr(trainer.model, "module"):
-            if hasattr(trainer.model.module, "on_epoch_end"):
-                trainer.model.module.on_epoch_end(trainer)
-        else:
-            if hasattr(trainer.model, "on_epoch_end"):
-                trainer.model.on_epoch_end(trainer)
-
-        if hasattr(trainer.criterion, "on_epoch_end"):
-            trainer.criterion.on_epoch_end(trainer)
-
-        if hasattr(trainer.optimizer, "on_epoch_end"):
-            trainer.optimizer.on_epoch_end(trainer)
-
-    @staticmethod
-    def on_train_step_start(trainer) -> None:
-        if hasattr(trainer.model, "module"):
-            if hasattr(trainer.model.module, "on_train_step_start"):
-                trainer.model.module.on_train_step_start(trainer)
-        else:
-            if hasattr(trainer.model, "on_train_step_start"):
-                trainer.model.on_train_step_start(trainer)
-
-        if hasattr(trainer.criterion, "on_train_step_start"):
-            trainer.criterion.on_train_step_start(trainer)
-
-        if hasattr(trainer.optimizer, "on_train_step_start"):
-            trainer.optimizer.on_train_step_start(trainer)
-
-    @staticmethod
-    def on_train_step_end(trainer) -> None:
-        if hasattr(trainer.model, "module"):
-            if hasattr(trainer.model.module, "on_train_step_end"):
-                trainer.model.module.on_train_step_end(trainer)
-        else:
-            if hasattr(trainer.model, "on_train_step_end"):
-                trainer.model.on_train_step_end(trainer)
-
-        if hasattr(trainer.criterion, "on_train_step_end"):
-            trainer.criterion.on_train_step_end(trainer)
-
-        if hasattr(trainer.optimizer, "on_train_step_end"):
-            trainer.optimizer.on_train_step_end(trainer)
-
-    @staticmethod
-    def on_keyboard_interrupt(trainer) -> None:
-        if hasattr(trainer.model, "module"):
-            if hasattr(trainer.model.module, "on_keyboard_interrupt"):
-                trainer.model.module.on_keyboard_interrupt(trainer)
-        else:
-            if hasattr(trainer.model, "on_keyboard_interrupt"):
-                trainer.model.on_keyboard_interrupt(trainer)
-
-        if hasattr(trainer.criterion, "on_keyboard_interrupt"):
-            trainer.criterion.on_keyboard_interrupt(trainer)
-
-        if hasattr(trainer.optimizer, "on_keyboard_interrupt"):
-            trainer.optimizer.on_keyboard_interrupt(trainer)
diff --git a/docs/source/extension/implementing_a_new_model.md b/docs/source/extension/implementing_a_new_model.md
index 2521789771..188f466c72 100644
--- a/docs/source/extension/implementing_a_new_model.md
+++ b/docs/source/extension/implementing_a_new_model.md
@@ -37,7 +37,7 @@
     an infinite flexibility to add custom behaviours for your model and training routines.
 
     For more details, see [BaseTTS](../main_classes/model_api.md#base-tts-model)
-    and `TTS.utils.callbacks`.
+    and [`trainer.callbacks`](https://github.com/idiap/coqui-ai-Trainer/blob/main/trainer/callbacks.py).
 
 6. Optionally, define `MyModelArgs`.